Verzia Consulting
Finance AI Diagnostic
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Finance AI Diagnostic

How much EBITDA is trapped in your manual finance processes?

24 research-backed questions. Six diagnostic dimensions. Scored against 2026 data from Deloitte, KPMG, MIT Sloan, HBR, and others. Find out exactly where AI can unlock value in your finance function — and what's blocking it.

5–25%
EBITDA improvement achievable with AI-enabled finance operations
74%
of companies report no tangible value from AI investments
80%
of AI ROI comes from Stage 1 & 2 — not advanced agents
93%
of leaders cite human factors — not tech — as the primary barrier
Your Context
Strategy & Leadership

Strategy & Leadership

Executive alignment, AI vision, and strategic prioritization. Research shows CFO sponsorship is the strongest single driver of successful adoption.

1Does your finance function have a clear AI vision aligned to the company's business strategy?
2Is there C-level or operating partner sponsorship for AI initiatives in finance?
3Have finance-relevant AI use cases been identified and prioritized against value creation levers (EBITDA, margin, cash flow)?
4Is finance collaborating with IT, data, and operations teams on AI initiatives?
1 / 6
Data Foundations

Data Foundations

Data quality, accessibility, governance, and integration readiness. MIT Sloan estimates 60–80% of project time is spent acquiring and cleaning data.

1Are your financial data sources accessible and consolidated (vs. trapped in siloed systems)?
2How reliable and accurate is your finance data? (Consider chart of accounts, cost centers, GL coding)
3Are your master data elements (chart of accounts, cost centers, vendor master) standardized across entities?
4Are there formal data governance and security policies for financial data?
2 / 6
Process & Automation

Process & Automation

Process standardization, current automation maturity, and AI opportunity mapping. Deloitte found only 30% of organizations redesign processes around AI.

1Are core finance processes (close, AP, AR, reporting, budgeting) standardized and documented?
2What level of automation currently exists in your finance workflows?
3Have you mapped which finance processes are suitable for AI augmentation?
4Can new AI solutions be integrated into your existing finance systems without major infrastructure work?
3 / 6
Technology & Infrastructure

Technology & Infrastructure

Cloud readiness, system capabilities, and integration maturity. Integration with legacy systems ranks as the top technical barrier at 49–55% across studies.

1What is your current ERP / financial system's readiness for AI integration?
2Do you have a BI / analytics layer that provides the foundation for AI models?
3How would you rate your team's current use of AI productivity tools (ChatGPT, Copilot, Claude, etc.)?
4Is your IT / cybersecurity team prepared to support AI tool deployment?
4 / 6
People & Skills

People & Skills

AI awareness, data literacy, change management, and upskilling capacity. HBR found that 80% of employees experience real anxiety about AI.

1Do your finance team members understand AI concepts and their relevance to finance work?
2How comfortable is your finance team with data and analytics tools beyond Excel?
3Is there a culture of innovation and openness to AI-driven change in the finance function?
4Are there structured upskilling or training programs to build AI capabilities?
5 / 6
Governance & Risk

Governance & Risk

AI risk management, compliance, auditability, and controls. Forbes found 73% of organizations say AI has exposed gaps in governance visibility.

1Have you assessed risks related to using AI in finance (bias, errors, hallucinations, data leakage)?
2Are your AI systems aligned with financial regulations and SOX / audit requirements?
3Are AI model decisions explainable and auditable?
4Does your organization have clear human-in-the-loop policies for AI-assisted finance decisions?
6 / 6
Your Diagnostic Results

Finance AI Value Map

0
of 120 possible
Level 1

Next Milestone

Unlock Your Full Value Map

Your overall score and maturity level are above. Your full report reveals the cross-dimensional risk patterns your score alone doesn't show, a cost-of-inaction projection, a prioritized 90-day roadmap, and the specific AI use cases matched to where you can unlock value fastest.

Risk Interaction Warnings Cost-of-Inaction Analysis 90-Day Roadmap Industry-Matched Insights ROI & Use Cases
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Dimension Analysis
Your scores vs. Level 4 target across all six pillars
Risk Interaction Analysis
Patterns across your dimensions that a simple score doesn't reveal — these are where AI initiatives actually stall
What the Research Says About Your Profile
Findings from 2026 studies matched to your specific score pattern and industry
The Cost of Waiting
The risk calculus has inverted in 2026 — the competitive risk of not deploying now exceeds the operational risk of deploying
Your 90-Day Roadmap
Prioritized actions based on your weakest dimensions
Priority AI Use Cases
Ranked by your readiness to execute — based on maturity level and dimension scores
Estimated Value Potential
Projected impact based on your team size and maturity — grounded in current research data
What Others at Your Level Are Doing
Real-world implementations matched to your maturity stage
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Next Step
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